About this role
Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish!
Our team is working toward a future where our devices are aware of us and our environment, they directly support our health and wellbeing, and they nudge us to be more thoughtful, present, and inspired human beings. We believe there is huge opportunity to improve lives and the world by understanding people, our activities, connections, and the environments we live in using sensing and machine learning on our devices.
Our team works with cross-functional partners across Apple to create high-impact features and new ways to interact on Apple Watch, home products, and new hardware. We prototype new experiences, develop and ship products, and publish our work. We are a creative, multi-disciplinary, optimistic, and collaborative team.
Come join us and build the future!
The team you will join is responsible for creating the technologies that power new, innovative product features for Apple Watch, like DoubleTap, AssistiveTouch, Handwashing, and Raise to Speak. We are highly collaborative and partner with a variety of research and product teams across Apple to explore novel experiences and ship features. We are looking for an ML engineer who is passionate about developing innovative product features that push the boundaries of sensing, machine learning, and human-computer interaction. You will work closely with designers, machine learning engineers, and software experts to turn vague, ambitious ideas into the next generation of sensing experiences for millions of Apple Watch users. Your responsibilities will include: * Train, evaluate, and debug deep learning models for complex tasks * Guide new features from early prototypes to shipping products, communicating with peers to build requirements and track progress
M.S. or Ph.D. in Machine Learning, Computer Science, or a related field; additional background in Human-Computer Interaction (HCI) is a plus Strong Python skills with experience working with deep learning frameworks such as PyTorch or TensorFlow Hands-on experience developing predictive models using time-series and multimodal sensor data Proficient in data collection, model training and optimization, defining metrics, and performing failure analysis Great communication and collaboration skills
Proven ability to design and build scalable modeling pipelines for data processing, training, and evaluation Experience with signal processing techniques for ML applications
Description
The team you will join is responsible for creating the technologies that power new, innovative product features for Apple Watch, like DoubleTap, AssistiveTouch, Handwashing, and Raise to Speak. We are highly collaborative and partner with a variety of research and product teams across Apple to explore novel experiences and ship features. We are looking for an ML engineer who is passionate about developing innovative product features that push the boundaries of sensing, machine learning, and human-computer interaction. You will work closely with designers, machine learning engineers, and software experts to turn vague, ambitious ideas into the next generation of sensing experiences for millions of Apple Watch users. Your responsibilities will include: * Train, evaluate, and debug deep learning models for complex tasks * Guide new features from early prototypes to shipping products, communicating with peers to build requirements and track progress
Minimum Qualifications
M.S. or Ph.D. in Machine Learning, Computer Science, or a related field; additional background in Human-Computer Interaction (HCI) is a plus Strong Python skills with experience working with deep learning frameworks such as PyTorch or TensorFlow Hands-on experience developing predictive models using time-series and multimodal sensor data Proficient in data collection, model training and optimization, defining metrics, and performing failure analysis Great communication and collaboration skills
Preferred Qualifications
Proven ability to design and build scalable modeling pipelines for data processing, training, and evaluation Experience with signal processing techniques for ML applications
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